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Comparing Erosion Risks from Forest Operations to Wildfire

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Comparing Erosion Risks from Forest Operations to Wildfire Comparing Erosion Risks from Forest Operations to Wildfire William J. Elliot Project Leader, USDA Forest Service, Rocky Mountain Research Station, Moscow, Idaho, Tel. 208 882 3557, Fax. 208 883 2318, Peter R. Robichaud Research Engineer , USDA Forest Service, Rocky Mountain Research Station, Moscow, Idaho, Tel. 208 882 3557, Fax. 208 883 2318, [email protected] Abstract - Wildfire and forest operations remove vegetation and disturb forest soils. Both of these effects can lead to an increased risk of soil erosion. Operations to reduce forest fuel loads, however, may reduce the risk of wildfire. This paper presents research and modeling results which show that under many conditions, carefully planned operations with adequate buffers, results in lower long-term erosion rates than experienced following wildfire, which is inevitable if fuel loads are not reduced. The effects of reducing fire-induced flood flows on forest stream systems, however, are unknown. Keywords. Soil Erosion, Forest operations, Forest fires, WEPP INTRODUCTION Forests provide numerous benefits for society, including fiber, wildlife, and recreation. Forest managers are challenged to balance ecosystem health and societal needs. During the first half of the last century, public forest management emphasized the harvesting of forest resources. In recent years, the emphasis in public forest management has been shifted to long-term sustainability. Fuel management is another issue that has recently become important. During most of the last century, fire suppression and timber harvest were the main fuel management practices. This has resulted in forests with an oversupply of fuels and diseased trees, leading to an increased risk of severe wildfires (Duncan 2001). Both fires and timber harvest increase soil erosion and sediment delivery from forest hillslopes. Soil erosion is one of the major concerns in current forest management. Soil erosion reduces upland forest productivity. Sediment from eroding hillslopes adversely affects water quality in forest streams, impacting the viability of aquatic ecosystems and numerous endangered aquatic species. Currently, managers are seeking to minimize erosion by applying improved management practices for forest operations and fuel management. One of the questions managers are seeking to answer is whether frequent forest operations cause more or less erosion than less frequent wildfires. The purpose of this paper is to compare erosion rates following forest disturbances to erosion rates following wildfires. FOREST EROSION PROCESSES In forests, soil erosion occurs from disturbances such as forest roads, timber harvesting, or fire. These disturbances have major affects on both the vegetation and the soil properties. Soil The International Mountain Logging and 11th Pacific Northwest Skyline Symposium 2001 78 erodibility depends on both the surface cover and the soil texture (Elliot and Hall 1997). The soil erodibility on a skid trail is greater than in the areas between skid trails, and the erodibility following a wildfire is much greater than in an undisturbed forest (Robichaud et al. 1993). Fire is a natural part of healthy forest ecosystems. In the past century, fire supression has resulted in reduced forest health, and an increase in fuel loads. Some managers suggest that this has resulted in an increase in high severity wildfires (Duncan 2001). After a fire or operation, forests are highly susceptible to erosion in the following year. They do, however, recover quickly as vegetation regrowth is rapid when smaller plants do not have to compete with trees for sunlight, nutrients, and water. For example, figure 1 shows the reduction in erosion rates following a wildfire in Eastern Oregon dropped about 90 percent the first year, with no erosion observed in year 4 on any of the slopes. 10 Percent Slope 1 20 30 60 0.1 Erosion (Mg/ha) 0.01 0.001 1234 Years after Fire Figure 1. Erosion rates measured following a wildfire in Eastern Oregon. Note log scale on y-axis (Robichaud and Brown 1999). Erosion in forests is highly variable, driven by a few extreme events each decade. Field data collected during years without events are likely to be well below "average" erosion rates, and data collected during a year with an event are likely to be well above the "average" rate. Eroded sediments are frequently deposited in stream channels where they may remain for years to decades, slowly moving through the stream system in response to high runoff events (Trimble 1999). Thus, the scale at which sedimentation is measured becomes important. Smaller scales will show large variations in erosion rates as disturbed sites recover, whereas watershed scale observations will tend to reflect long-term trends in erosion rates, with large sedimentation events associated with infrequent watershed disturbances or flood events. The International Mountain Logging and 11th Pacific Northwest Skyline Symposium 2001 79 Managers and the public tend to focus on the erosion that may occur immediately following a disturbance, and fail to consider medium- or long-term impacts of short-term disturbances. EROSION PREDICTION Prediction of soil erosion by water is a common practice for natural resource managers for evaluating impacts of upland erosion on soil productivity and offsite water quality. Erosion prediction methods are used to evaluate different management practices and control techniques. One of the prediction tools recently developed is the Water Erosion Prediction Project (WEPP; Flanagan and Livingston 1995). WEPP is a physically-based soil erosion model, and is particularly suited to modeling the conditions common in forests. Forest templates were developed for the model (Elliot and Hall, 1997) and later, a user-friendly suite of Internet interfaces called FS-WEPP (Elliot et al. 2000). Included with these interfaces is a database of typical forest soil and vegetation conditions. These databases were populated with values determined from rainfall simulation and natural rainfall field research by scientists within our organization and elsewhere. Cover is one of the most important factors in determining soil erosion rate. The WEPP model does not have a cover value for an input, but instead calculates the amount of cover each day as a function of vegetation growth and residue decomposition values in response to the climate. In the WEPP model, the hillslope can have a complex shape, and can include numerous soils and vegetation types along the hillslope. Each unique combination of soil and vegetation is called an overland flow element (OFE) (Figure 2). This feature allows users to describe disturbed forest conditions with undisturbed forest buffers. OFE 1 OFE 2 OFE 3 Figure 2. Overland flow elements (OFEs). OFE 1 has soil 1 and management 1, OFE 2 has soil 2 and management 1, and OFE 3 has soil 2 and management 2. FS WEPP INTERFACES Two Internet interfaces have been developed for WEPP for forest conditions (Elliot et al. 2000). One is for a number of road scenarios (WEPP:Road), and the other for disturbed forest conditions (Disturbed WEPP). A complementary interface (Rock Clime) assists the user in selecting an appropriate climate from a large climate database, or to customize the mean monthly precipitation amounts, number of wet days per month, and monthly mean maximum and minimum temperatures (Scheele et al. 2001). Disturbed WEPP. We are developing Disturbed WEPP for forest conditions including prescribed fires, wild fires, and young and mature forest. Disturbed WEPP currently allows two The International Mountain Logging and 11th Pacific Northwest Skyline Symposium 2001 80 OFEs (Figure 2) so that users can study numerous combinations of uphill and downhill disturbances, such as a harvest area above a buffer zone. The user can select the climate and soil, the vegetation type and surface cover on the two OFEs, and the topography for each OFE. To aid users in ensuring the desired amount of cover, Disturbed WEPP allows the user to calibrate WEPP to achieve the desired cover on each OFE. The output presents the probability associated with years with exceptionally high runoff and erosion as well as a mean annual erosion rate that would occur in a year with an "average" climate. A recent validation study (Elliot and Foltz 2001) found that when parameterized for forest conditions, the Disturbed WEPP model was able to predict soil erosion following prescribed and wildfire and disturbed forests (Tables 1 and 2). VALIDATION RESULTS AND DISCUSSION We have completed a number of studies on erosion following prescribed and wildfire, and have identified several studies of erosion following forest operations. For our validation, we used the Rock:Clime interface to describe a climate as close to the reported weather as we could. We used as much soil and topographic data as we could determine from each reference. Erosion After Fire. Table 1 summarizes studies on hillslope erosion rates following fire. Elliot et al. (1996) reported an erosion rate between 0.5 and 1 Mg ha-1 following a prescribed fire in central Idaho. The site had experienced a low severity prescribed fire and had a skid trail at the bottom of the slope. It appeared that most of the sediment was generated from this short width of skid trail. The predicted values were similar to the observed. On a prescribed fire study in Montana, Robichaud (1998) observed very low erosion rates the year following the prescribed fire, but a greater rate the second and third years. The first year (1995) was a year of low snowfall, likely the reason for the low erosion rate. The second year was a particularly wet year, resulting in increased erosion even though the vegetation had recovered. The third year, the effects of increased vegetation were apparent with the decreasing erosion rate. After specifying the cover for a different vegetation class and increased cover, Disturbed WEPP predicted values similar to the observed values in years 2 and 3. The predicted erosion rates following wild fire reported in Robichaud and Brown (1999) were within the confidence limits of the field observations (Elliot and Foltz 2001).
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